5 Archaeobotany
The results presented here are preliminary and the chapter has yet to be written.
In this chapter, I will present the macrobotanical data from 170 case studies used to carry on this research (Chapter 3), along with the quantifications performed on the absolute counts. The data will be first presented temporally, and a discussion of the diachronic trends will follow at the end of the chapter.
5.1 Case studies
The following map shows the sites under investigation, divided by chronology. Please select the desired chronology (or chronologies) from the legend on the right.
R = Roman, LR = Late Roman, EMA = Early Middle Ages, Ma = 11th c. onwards5.2 Ubiquity
In Chapter 4 ubiquity has been described as the best way to present the archaeobotanical remains from the Italian peninsula, given the numerous biases in the samples. The heatmap below (Figure 5.2) provides a good overview of the temporal trends of presence of cereals, legumes, fruits and nuts in the entire area under examination.
Show the code
# Load the libraries
# Note: these libraries are used for the data visualizations in this page.
library(RColorBrewer)
library(reshape2)
library(ggplot2)
library(hrbrthemes)
library(plotly)
library(patchwork)
## UBIQUITY
## Creating a dataframe that contains the ubiquity of each century under examination.
Ubiquity_table <- data.frame(
"I BCE" = archaeobotany_tables(plants_export, -1)$Ubiquity_exp,
"I CE" = archaeobotany_tables(plants_export, 1)$Ubiquity_exp,
"II CE" = archaeobotany_tables(plants_export, 2)$Ubiquity_exp,
"III CE" = archaeobotany_tables(plants_export, 3)$Ubiquity_exp,
"IV CE" = archaeobotany_tables(plants_export, 4)$Ubiquity_exp,
"V CE" = archaeobotany_tables(plants_export, 5)$Ubiquity_exp,
"VI CE" = archaeobotany_tables(plants_export, 6)$Ubiquity_exp,
"VII CE" = archaeobotany_tables(plants_export, 7)$Ubiquity_exp,
"VIII CE" = archaeobotany_tables(plants_export, 8)$Ubiquity_exp,
"IX CE" = archaeobotany_tables(plants_export, 9)$Ubiquity_exp,
"X CE" = archaeobotany_tables(plants_export, 10)$Ubiquity_exp,
"XI CE" = archaeobotany_tables(plants_export, 11)$Ubiquity_exp
)
# Transform the ubiquity table into a matrix
Ubiquity_mat <- as.matrix(Ubiquity_table)
# Rename the centuries
colnames(Ubiquity_mat) <- c("1st c. BCE", "1st c. CE", "2nd c. CE",
"3rd c. CE", "4th c. CE", "5th c. CE",
"6th c. CE", "7th c. CE", "8th c. CE",
"9th c. CE", "10th c. CE", "11th c. CE")
# The data has to be molten to use it with ggplot2
# (package: reshape2)
Ubiquity_melt <- melt(Ubiquity_mat)
# Let's now rename the columns
colnames(Ubiquity_melt) <- c("Taxon", "Century", "Ubiquity")
# Add a column for the text tooltip
Ubiquity_melt <- Ubiquity_melt %>%
mutate(text = paste0("Taxon: ", Taxon, "\n", "Century: ", Century, "\n", "Value: ",round(Ubiquity,2)))
# Create the heatmap with ggplot2
Ubiquity_HM <- ggplot(Ubiquity_melt, aes(Century, Taxon, fill=Ubiquity, text=text)) +
geom_tile(colour="white") +
scale_alpha(range=c(0,1)) +
scale_x_discrete("", expand = c(0, 0)) +
scale_y_discrete("", expand = c(0, 0)) +
theme_grey(base_size = 9) +
theme(legend.position = "right",
axis.ticks = element_blank(),
axis.text.x = element_text(angle = 90, hjust = 0)
) +
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())+
labs(
title="Ubiquity",
subtitle="Diachronical heatmap of recorded plant species"
) +
scale_fill_gradient(low = "white", high = "black")5.2.1 Macroregional differences
The heatmap displayed in Figure 5.2 presents diachronical ubiquity values of the entire peninsula. However, it is also possible to look at the macroregional differences in plants ubiquities. The R function Ubiquity_macroreg_chrono() (Section 1.3) was created to subset data related to (current) Northern, Central and Southern Italian regions. Subsetting the dataset required a larger chronological division to obtain enough sites for a statistical interpretation of the results. The ubiquity values are presented using the variable Chronology rather than the individual centuries. For a clearer reading of the plot, the taxa have been divided into–Cereals, Pulses and Fruits/Nuts. Some taxa have been omitted from the plot.
Show the code: data preparation
# Ubiquity by Italian Macro regions: Northern, Central and Southern Italy
# Load the libraries
library(vegan)
library(matrixStats)
library(patchwork)
# Creating a dataframe with the ubiquities of all macroregions and chronologies
bot_macroreg <- rbind(
Ubiquity_R_NI <- Ubiquity_macroreg_chrono(Archaeobot_Condensed,"Northern Italy", "R"),
Ubiquity_R_CI <- Ubiquity_macroreg_chrono(Archaeobot_Condensed,"Central Italy", "R"),
Ubiquity_R_SI <- Ubiquity_macroreg_chrono(Archaeobot_Condensed,"Southern Italy", "R"),
Ubiquity_LR_NI <- Ubiquity_macroreg_chrono(Archaeobot_Condensed,"Northern Italy", "LR"),
Ubiquity_LR_CI <- Ubiquity_macroreg_chrono(Archaeobot_Condensed,"Central Italy", "LR"),
Ubiquity_LR_SI <- Ubiquity_macroreg_chrono(Archaeobot_Condensed,"Southern Italy", "LR"),
Ubiquity_EMA_NI <- Ubiquity_macroreg_chrono(Archaeobot_Condensed,"Northern Italy", "EMA"),
Ubiquity_EMA_CI <- Ubiquity_macroreg_chrono(Archaeobot_Condensed,"Central Italy", "EMA"),
Ubiquity_EMA_SI <- Ubiquity_macroreg_chrono(Archaeobot_Condensed,"Southern Italy", "EMA"),
Ubiquity_Ma_NI <- Ubiquity_macroreg_chrono(Archaeobot_Condensed,"Northern Italy", "Ma"),
Ubiquity_Ma_CI <- Ubiquity_macroreg_chrono(Archaeobot_Condensed,"Central Italy", "Ma"),
Ubiquity_Ma_SI <- Ubiquity_macroreg_chrono(Archaeobot_Condensed,"Southern Italy", "Ma")
)
# Re-arranging the cereals/macroregions for visualisation on the Y axis
level_macroreg_order <- c("Southern Italy", "Central Italy", "Northern Italy")
level_cereals_order <- c("Common.Wheat", "Barley", "Rye",
"Einkorn", "Emmer", "Proso.millet",
"Foxtail.millet", "Oats", "Sorghum")
# Cereals
cer_ubiquity_macroreg.R <- filter(bot_macroreg, Chronology=="R" & Plant.Type=="Cereals")
cer_ubiquity_macroreg.R <- filter(cer_ubiquity_macroreg.R, Macroregion!="Central Italy")
cer_ubiquity_macroreg.LR <- filter(bot_macroreg, Chronology=="LR" & Plant.Type=="Cereals")
cer_ubiquity_macroreg.EMA <- filter(bot_macroreg, Chronology=="EMA" & Plant.Type=="Cereals")
cer_ubiquity_macroreg.Ma <- filter(bot_macroreg, (Chronology=="Ma" & Plant.Type=="Cereals"))
cer_ubiquity_macroreg.Ma <- filter(cer_ubiquity_macroreg.Ma, Macroregion!="Southern Italy")
#Pulses
puls_ubiquity_macroreg.R <- filter(bot_macroreg, Chronology=="R" & Plant.Type=="Pulses")
puls_ubiquity_macroreg.R <- filter(puls_ubiquity_macroreg.R, Macroregion!="Central Italy")
puls_ubiquity_macroreg.R <- filter(puls_ubiquity_macroreg.R, Plant!="Chickpea")
puls_ubiquity_macroreg.LR <- filter(bot_macroreg, Chronology=="LR" & Plant.Type=="Pulses")
puls_ubiquity_macroreg.LR <- filter(puls_ubiquity_macroreg.LR,
Macroregion!="Southern Italy")
puls_ubiquity_macroreg.LR <- filter(puls_ubiquity_macroreg.LR, Plant!="Chickpea")
puls_ubiquity_macroreg.EMA <- filter(bot_macroreg, Chronology=="EMA" & Plant.Type=="Pulses")
puls_ubiquity_macroreg.Ma <- filter(bot_macroreg, Chronology=="Ma" & Plant.Type=="Pulses")
puls_ubiquity_macroreg.Ma <- filter(puls_ubiquity_macroreg.Ma,
Macroregion!="Southern Italy")
#Fruits (+ Subset)
fnuts_ubiquity_macroreg.R <- filter(bot_macroreg, Chronology=="R" & Plant.Type=="Fruits/Nuts")
fnuts_ubiquity_macroreg.R <- subset(fnuts_ubiquity_macroreg.R, (Plant == "Wild.Cherry" | Plant == "Walnut" | Plant == "Peach" | Plant == "Olive" |Plant == "Grape" | Plant =="Fig" | Plant =="Apple"))
fnuts_ubiquity_macroreg.R <- filter(fnuts_ubiquity_macroreg.R, Macroregion!="Central Italy")
fnuts_ubiquity_macroreg.LR <- filter(bot_macroreg, Chronology=="LR" & Plant.Type=="Fruits/Nuts")
fnuts_ubiquity_macroreg.LR <- subset(fnuts_ubiquity_macroreg.LR, (Plant == "Wild.Cherry" | Plant == "Walnut" | Plant == "Peach" | Plant == "Olive" |Plant == "Grape" | Plant =="Fig" | Plant =="Apple"))
fnuts_ubiquity_macroreg.EMA <- filter(bot_macroreg, Chronology=="EMA" & Plant.Type=="Fruits/Nuts")
fnuts_ubiquity_macroreg.EMA <- subset(fnuts_ubiquity_macroreg.EMA, (Plant == "Wild.Cherry" | Plant == "Walnut" | Plant == "Peach" | Plant == "Olive" |Plant == "Grape" | Plant =="Fig" | Plant =="Apple"))
fnuts_ubiquity_macroreg.Ma <- filter(bot_macroreg, Chronology=="Ma" & Plant.Type=="Fruits/Nuts")
fnuts_ubiquity_macroreg.Ma <- subset(fnuts_ubiquity_macroreg.Ma, (Plant == "Wild.Cherry" | Plant == "Walnut" | Plant == "Peach" | Plant == "Olive" |Plant == "Grape" | Plant =="Fig" | Plant =="Apple"))
fnuts_ubiquity_macroreg.Ma <- filter(fnuts_ubiquity_macroreg.Ma, Macroregion!="Southern Italy")Show the code: plots
# Cereals plots ubiquity
cer_ubiquity_macroreg_R.HM <- ggplot(cer_ubiquity_macroreg.R, aes(
factor(Macroregion, levels=(level_macroreg_order)),
factor(Plant, levels=rev(level_cereals_order)),
fill=(Ubiquity)
)) +
geom_tile(colour="white") +
geom_text(aes(label = Ubiquity), colour="white", size=3)+
scale_alpha(range=c(0,1)) +
scale_x_discrete("", expand = c(0, 0)) +
scale_y_discrete("", expand = c(0, 0)) +
theme_grey(base_size = 9) +
theme(legend.position = "none",
axis.ticks = element_blank()
) +
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())+
labs(
title="Roman"
) + scale_fill_gradient(low = "white", high = "black")
cer_ubiquity_macroreg_LR.HM <- ggplot(cer_ubiquity_macroreg.LR, aes(
factor(Macroregion, levels=(level_macroreg_order)),
factor(Plant, levels=rev(level_cereals_order)),
fill=(Ubiquity)
)) +
geom_tile(colour="white") +
geom_text(aes(label = Ubiquity), colour="white", size=3)+
scale_alpha(range=c(0,1)) +
scale_x_discrete("", expand = c(0, 0)) +
scale_y_discrete("", expand = c(0, 0)) +
theme_grey(base_size = 9) +
theme(legend.position = "none",
axis.ticks = element_blank()
) +
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())+
labs(
title="Late Roman"
) + scale_fill_gradient(low = "white", high = "black")
cer_ubiquity_macroreg_EMA.HM <- ggplot(cer_ubiquity_macroreg.EMA, aes(
factor(Macroregion, levels=(level_macroreg_order)),
factor(Plant, levels=rev(level_cereals_order)),
fill=(Ubiquity)
)) +
geom_tile(colour="white") +
geom_text(aes(label = Ubiquity), colour="white", size=3)+
scale_alpha(range=c(0,1)) +
scale_x_discrete("", expand = c(0, 0)) +
scale_y_discrete("", expand = c(0, 0)) +
theme_grey(base_size = 9) +
theme(legend.position = "none",
axis.ticks = element_blank()
) +
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())+
labs(
title="Early Medieval"
) + scale_fill_gradient(low = "white", high = "black")
cer_ubiquity_macroreg_Ma.HM <- ggplot(cer_ubiquity_macroreg.Ma, aes(
factor(Macroregion, levels=(level_macroreg_order)),
factor(Plant, levels=rev(level_cereals_order)),
fill=(Ubiquity)
)) +
geom_tile(colour="white") +
geom_text(aes(label = Ubiquity), colour="white", size=3)+
scale_alpha(range=c(0,1)) +
scale_x_discrete("", expand = c(0, 0)) +
scale_y_discrete("", expand = c(0, 0)) +
theme_grey(base_size = 9) +
theme(legend.position = "none",
axis.ticks = element_blank()
) +
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())+
labs(
title="Medieval"
) + scale_fill_gradient(low = "white", high = "black")
Cereals_Ubiquity_MacroReg_Patchwork <- (cer_ubiquity_macroreg_R.HM|cer_ubiquity_macroreg_LR.HM)/(cer_ubiquity_macroreg_EMA.HM|cer_ubiquity_macroreg_Ma.HM)
Cereals_Ubiquity_MacroReg_Patchwork + plot_annotation(
title = 'Cereals',
subtitle = 'Ubiquity (%), plotted by macroregion and chronology.',
caption='Note: Data was too scarce for Roman Central Italy and Medieval Southern Italy.'
)Show the code: plots
# Pulses plots ubiquity
puls_ubiquity_macroreg_R.HM <- ggplot(puls_ubiquity_macroreg.R, aes(
factor(Macroregion, levels=(level_macroreg_order)),
Plant,
fill=(Ubiquity)
)) +
geom_tile(colour="white") +
geom_text(aes(label = Ubiquity), colour="#cfcfcf", size=3)+
scale_alpha(range=c(0,1)) +
scale_x_discrete("", expand = c(0, 0)) +
scale_y_discrete("", expand = c(0, 0)) +
theme_grey(base_size = 9) +
theme(legend.position = "none",
axis.ticks = element_blank()
) +
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())+
labs(
title="Roman"
) + scale_fill_gradient(low = "white", high = "black")
puls_ubiquity_macroreg_LR.HM <- ggplot(puls_ubiquity_macroreg.LR, aes(
factor(Macroregion, levels=(level_macroreg_order)),
Plant,
fill=(Ubiquity)
)) +
geom_tile(colour="white") +
geom_text(aes(label = Ubiquity), colour="#ffffff", size=3)+
scale_alpha(range=c(0,1)) +
scale_x_discrete("", expand = c(0, 0)) +
scale_y_discrete("", expand = c(0, 0)) +
theme_grey(base_size = 9) +
theme(legend.position = "none",
axis.ticks = element_blank()
) +
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())+
labs(
title="Late Roman"
) + scale_fill_gradient(low = "white", high = "black")
puls_ubiquity_macroreg_EMA.HM <- ggplot(puls_ubiquity_macroreg.EMA, aes(
factor(Macroregion, levels=(level_macroreg_order)),
Plant,
fill=(Ubiquity)
)) +
geom_tile(colour="white") +
geom_text(aes(label = Ubiquity), colour="white", size=3)+
scale_alpha(range=c(0,1)) +
scale_x_discrete("", expand = c(0, 0)) +
scale_y_discrete("", expand = c(0, 0)) +
theme_grey(base_size = 9) +
theme(legend.position = "none",
axis.ticks = element_blank()
) +
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())+
labs(
title="Early Medieval"
) + scale_fill_gradient(low = "white", high = "black")
puls_ubiquity_macroreg_Ma.HM <- ggplot(puls_ubiquity_macroreg.Ma, aes(
factor(Macroregion, levels=(level_macroreg_order)),
Plant,
fill=(Ubiquity)
)) +
geom_tile(colour="white") +
geom_text(aes(label = Ubiquity), colour="white", size=3)+
scale_alpha(range=c(0,1)) +
scale_x_discrete("", expand = c(0, 0)) +
scale_y_discrete("", expand = c(0, 0)) +
theme_grey(base_size = 9) +
theme(legend.position = "none",
axis.ticks = element_blank()
) +
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())+
labs(
title="Medieval"
) + scale_fill_gradient(low = "white", high = "black")
Pulses_Ubiquity_MacroReg_Patchwork <- (puls_ubiquity_macroreg_R.HM|puls_ubiquity_macroreg_LR.HM)/(puls_ubiquity_macroreg_EMA.HM|puls_ubiquity_macroreg_Ma.HM)
Pulses_Ubiquity_MacroReg_Patchwork + plot_annotation(
title = 'Pulses',
subtitle = 'Ubiquity (%), plotted by macroregion and chronology.',
caption='Note: Data was too scarce for Roman Central Italy and Late Roman/Medieval Southern Italy.'
)Show the code: plots
# Fruits nuts plots
fnuts_ubiquity_macroreg_R.HM <- ggplot(fnuts_ubiquity_macroreg.R, aes(
factor(Macroregion, levels=(level_macroreg_order)),
Plant,
fill=(Ubiquity)
)) +
geom_tile(colour="white") +
geom_text(aes(label = Ubiquity), colour="white", size=3)+
scale_alpha(range=c(0,1)) +
scale_x_discrete("", expand = c(0, 0)) +
scale_y_discrete("", expand = c(0, 0)) +
theme_grey(base_size = 9) +
theme(legend.position = "none",
axis.ticks = element_blank()
) +
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())+
labs(
title="Roman"
) + scale_fill_gradient(low = "white", high = "black")
fnuts_ubiquity_macroreg_LR.HM <- ggplot(fnuts_ubiquity_macroreg.LR, aes(
factor(Macroregion, levels=(level_macroreg_order)),
Plant,
fill=(Ubiquity)
)) +
geom_tile(colour="white") +
geom_text(aes(label = Ubiquity), colour="white", size=3)+
scale_alpha(range=c(0,1)) +
scale_x_discrete("", expand = c(0, 0)) +
scale_y_discrete("", expand = c(0, 0)) +
theme_grey(base_size = 9) +
theme(legend.position = "none",
axis.ticks = element_blank()
) +
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())+
labs(
title="Late Roman"
) + scale_fill_gradient(low = "white", high = "black")
fnuts_ubiquity_macroreg_EMA.HM <- ggplot(fnuts_ubiquity_macroreg.EMA, aes(
factor(Macroregion, levels=(level_macroreg_order)),
Plant,
fill=(Ubiquity)
)) +
geom_tile(colour="white") +
geom_text(aes(label = Ubiquity), colour="white", size=3)+
scale_alpha(range=c(0,1)) +
scale_x_discrete("", expand = c(0, 0)) +
scale_y_discrete("", expand = c(0, 0)) +
theme_grey(base_size = 9) +
theme(legend.position = "none",
axis.ticks = element_blank()
) +
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())+
labs(
title="Early Medieval"
) + scale_fill_gradient(low = "white", high = "black")
fnuts_ubiquity_macroreg_Ma.HM <- ggplot(fnuts_ubiquity_macroreg.Ma, aes(
factor(Macroregion, levels=(level_macroreg_order)),
Plant,
fill=(Ubiquity)
)) +
geom_tile(colour="white") +
geom_text(aes(label = Ubiquity), colour="white", size=3)+
scale_alpha(range=c(0,1)) +
scale_x_discrete("", expand = c(0, 0)) +
scale_y_discrete("", expand = c(0, 0)) +
theme_grey(base_size = 9) +
theme(legend.position = "none",
axis.ticks = element_blank()
) +
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())+
labs(
title="Medieval"
) + scale_fill_gradient(low = "white", high = "black")
FrNuts_Ubiquity_MacroReg_Patchwork <- (fnuts_ubiquity_macroreg_R.HM|fnuts_ubiquity_macroreg_LR.HM)/(fnuts_ubiquity_macroreg_EMA.HM|fnuts_ubiquity_macroreg_Ma.HM)
FrNuts_Ubiquity_MacroReg_Patchwork + plot_annotation(
title = 'Fruits/Nuts',
subtitle = 'Ubiquity (%), plotted by macroregion and chronology.',
caption='Note: Data was too scarce for Roman Central Italy and Medieval Southern Italy.'
)5.2.1.1 Cereals
It is interesting to notice how in the Roman age, cereals are similarly ubiquitous in Southern and Northern Italy, although there are some exceptions (i.e. einkorn, rye, oats, proso millet) that can derive from the randomness of samples. Unfortunately, only three sites provided botanical samples for Roman Central Italy and the values have been omitted from the plot. These sites (from the Roman Peasant Project, Tuscany) only reported three kinds of cereal: common wheat, emmer, and barley. Similar ubiquity values for the two macroregions under assessment in the Roman age may suggest similar production patterns in the whole peninsula. In the Late Roman age, ubiquity data has been calculated for the three macroregions. Three crops are found on 62-75% of the Central Italian sites: common wheat, barley and emmer. Other cereals are present, but less ubiquitously. These three cultivations seem to be diffused in the south as well. Conversely, in Northern Italy common wheat and barley were important cultivations but competed with other cereals including millet, sorghum, and rye (now doubled in presence). The Early Medieval age seems to mark a shift in agricultural practices—cereals ubiquities vary more markedly in the three macroregions. In Southern Italy, common wheat and barley were still the predominant cereals. This is true for Central and Northern Italy, however in these regions other cereals are also widely present in a large number of sites. The samples from the Medieval age are fewer in number since the upper boundary of this project’s chronology is the 11th c. Despite the short chronology, it is possible to make some considerations. Medieval Centraly Italy relied heavily on common wheat, barley and emmer, with other cereals increasingly important. Barley is the most ubiquitous cereal in Northern Italy in this period, followed by common wheat, millets and sorghum.
5.2.1.2 Pulses
In the Roman Age, pulses are an important part of the diet and are cultivated both in Northern and Southern Italy. In the latter, vetch/broad beans are present in 22-32% of the samples, and lentils are present in 38% of the sites. In the Late Roman Age, broad beans are equally important in Central and Northern Italy, and peas are present in 50% of the Central Italian sites. In the Early Medieval Age, pulses are present in many Central Italian sites, especially blue/red peas, broad beans and other Fabaceae. Lentils and broad beans are also cultivated in almost half of the Northern Italian sites. The importance of pulses in Central Italy is confirmed by the 11th c. samples, where every specie is present in over 66% of the sites and Fabaceae and blue/red peas are found in every sample. Conversely, in Northern Italy broad bean is found in 66% of the sites.
5.2.1.3 Fruits and nuts
Olive and grape are two essential cultivations in the Italian peninsula. Olive pits, as can be expected, are more ubiquitous in Southern Italy, where in Roman times are present in >87% of the sites and in over 58% of the sites in the following chronologies1. Conversely, the grape is important in Central and Northern Italy in the Late Roman, Early Medieval and Medieval ages.
5.3 Richness and diversity
5.3.1 Richness and diversity in the Italian macroregions
Show the code: data preparation
# Species richness based on geographical features
# RELATIVE PROPORTIONS OF ARCHAEOBOT_VIZ QUERY EXPORT FROM THE DB
# (Condensed, without totals)
# Remove NAs
Df_Cond_Plants[is.na(Df_Cond_Plants)] <-0
# Generate a dataframe with the relative proportions and round the results
Df_Cond_Plants_Rel <- decostand(Df_Cond_Plants[11:50], method = "total")
Df_Cond_Plants_Rel <- round(Df_Cond_Plants_Rel, digits=2)
# Add more info to the dataframe
Df_Cond_Plants_Rel_Richness_Diversity <- data.frame(
"Geo" = Df_Cond_Plants$Geo,
"Chronology" = Df_Cond_Plants$Chronology,
"Type"= Df_Cond_Plants$Type,
"Specnumber" = specnumber(Df_Cond_Plants_Rel),
"Shannon Div" = diversity(Df_Cond_Plants_Rel),
Df_Cond_Plants_Rel
)
Df_Cond_Plants_Rel_withMacroregion <- data.frame("Geo" = Df_Cond_Plants$Geo,
"Chronology" = Df_Cond_Plants$Chronology,
"Type"= Df_Cond_Plants$Type,
"Macroregion" = Df_Cond_Plants$name_macroreg,
"Specnumber" = specnumber(Df_Cond_Plants_Rel[1:10]), #Only cereals
"Shannon Div" = diversity(Df_Cond_Plants_Rel[1:10]),
Df_Cond_Plants_Rel[1:10]
)
# Let's plot the diversity by macroregion
# Creating the dataframes for R and EMA age
# I know it's called "Plants" but it's actually just cereals
Df_Cond_Plants_Rel_withMacroregion.R <- filter(Df_Cond_Plants_Rel_withMacroregion, Chronology == "R")
Df_Cond_Plants_Rel_withMacroregion.LR <- filter(Df_Cond_Plants_Rel_withMacroregion, Chronology == "LR")
Df_Cond_Plants_Rel_withMacroregion.EMA <- filter(Df_Cond_Plants_Rel_withMacroregion, Chronology == "EMA")Show the code: plots
pal_RichnessvsGeo <- c("cadetblue3", "gold1", "bisque4", "palegreen4")
plot_RichnessMacroReg.R <- ggplot(Df_Cond_Plants_Rel_withMacroregion.R, aes(x = Macroregion, y = Specnumber, fill = Macroregion)) +
geom_violin(trim=FALSE) +
geom_boxplot(width=0.1, fill="white")+
scale_fill_manual(values = pal_RichnessvsGeo) +
geom_jitter(alpha=0.3)+
scale_x_discrete(labels = c("Central Italy \n (n = 3)", "Northern Italy \n (n = 39)", "Southern Italy \n (n=31)")) +
theme(legend.position = "none",
plot.background = element_rect("white"),
panel.background = element_rect("white"),
panel.grid = element_line("grey90"),
axis.line = element_line("gray25"),
axis.text = element_text(size = 12, color = "gray25"),
axis.title = element_text(color = "gray25"),
legend.text = element_text(size = 12)) +
labs(x = "Macroregion",
y = "Number of species per site",
title = "R - Cereal richness")
plot_RichnessMacroReg.EMA <- ggplot(Df_Cond_Plants_Rel_withMacroregion.EMA, aes(x = Macroregion, y = Specnumber, fill = Macroregion)) +
geom_violin(trim=FALSE) +
geom_boxplot(width=0.1, fill="white")+
scale_fill_manual(values = pal_RichnessvsGeo) +
geom_jitter(alpha=0.3)+
scale_x_discrete(labels = c("Central Italy \n (n = 10)", "Northern Italy \n (n = 36)", "Southern Italy \n (n=17)")) +
theme(legend.position = "none",
plot.background = element_rect("white"),
panel.background = element_rect("white"),
panel.grid = element_line("grey90"),
axis.line = element_line("gray25"),
axis.text = element_text(size = 12, color = "gray25"),
axis.title = element_text(color = "gray25"),
legend.text = element_text(size = 12)) +
labs(x = "Macroregion",
y = "Number of species per site",
title = "EMA - Cereal richness")Cereals share similar presence values in Roman Northern and Southern Italian sites (Figure 5.6). Central Italy reports higher values, although this is based only on three sites and hence it is not reliable. During the Early Middle Ages, Central Italy again is the richest in cereals, closely followed by Northern Italy. Interestingly, Southern Italy still reports values very close to the Roman age. A full list of the Southern Italian EMA sites is reported in Table 5.1.
| ID | Site | Region | Geography | Type | Culture/Influence |
|---|---|---|---|---|---|
| 98 | S. Maria in Cività, D85 | Molise | Hilltop | Urban | Lombard |
| 107 | S. Giovanni di Ruoti, Phase 3A | Basilicata | Mountain | Monastery | Lombard |
| 107 | S. Giovanni di Ruoti, Phase 3B | Basilicata | Mountain | Monastery | Lombard |
| 198 | Salapia, area botteghe, US 2475 | Puglia | Coast/Lagoon | Urban | Lombard |
| 198 | Salapia, area botteghe, US 2437 | Puglia | Coast/Lagoon | Urban | Lombard |
| 199 | Salapia, area conceria, US 2054 | Puglia | Coast/Lagoon | Urban | Lombard |
| 199 | Salapia, area conceria, US 2211-2217 | Puglia | Coast/Lagoon | Urban | Lombard |
| 199 | Salapia, area conceria, 8th-9th c. | Puglia | Coast/Lagoon | Urban | Lombard |
| 196 | Faragola, wastepit 61 | Puglia | Plain | Rural, villa | Lombard |
| 196 | Faragola, wastepit 66 | Puglia | Plain | Rural, villa | Lombard |
| 234 | Colle Castellano, Phase 3-4 | Molise | Hill | Urban | Lombard |
| 177 | San Vincenzo al Volturno, kitchen area | Molise | Hill | Monastery | Lombard |
| 101 | Supersano, loc. Scorpo | Puglia | Plain | Rural | Byzantine |
| 250 | Apigliano, 9th-10th c., pits | Puglia | Plain | Rural | Byzantine |
| 250 | Apigliano, 10th-11th c., pits | Puglia | Plain | Rural | Byzantine |
| 196 | Faragola, granary A7 | Puglia | Plain | Rural, villa | Lombard |
| 196 | Faragola, granary A8 | Puglia | Plain | Rural, villa | Lombard |
5.4 Cereals regionality: testing the results
Describe the PERMANOVA etc
5.4.1 Network Analysis of cereals in EMA sites
The Late Roman values for Southern Italy are only based on 5 samples (3 of which are from the same site, Salapia) so the values are not very trustworthy.↩︎